Elasticsearch-07-Elasticsearch Java API Client-Elasticsearch 8.0 的高阶api

文章目录

es8 API基础配置和bean注入
高阶使用
- 1：引入elasticsearchClient
- 2：查询所有索引
- 3：查询某个索引
- 4:创建索引
- 5:删除指定索引
- 6:查询索引的映射
- 7:创建索引指定映射
- 8:创建文档
- - 使用HashMap作为数据存储容器
  - 使用自定义类作为数据存储容器
  - 使用外部JSON数据创建
- 9: 查询所有文档
- 10:根据ID查询文档
- 11:删除文档
- 12:修改文档
- - 全覆盖
  - 修改部分文档
- 13:批量操作
- - 批量新增
  - 批量删除
  - 批量更新
DSL查询
- 1：matchAll查询所有文档
- 2:match 根据字段查询
- 3:多id查询
- 4:term 不分词查询
- 5:范围查询
- 6: 前缀查询
- 7:匹配查询
- - //匹配查询
  - ?单字符匹配
- 8:模糊查询
- 9:多条件查询
- 10：多字段查询-multiMatch
- 11:高亮显示
- 12:分页查询
- 12-1：使用分页时，最多返回10000条。需要进行设置
- 13:排序
- 14:指定字段查询
- 15:聚合查询-求最大值
- 16:桶聚合查询-劣势 group by

es8 API基础配置和bean注入

Elasticsearch-06-Elasticsearch Java API Client-Elasticsearch 8.0 的基础配置和使用

高阶使用

1：引入elasticsearchClient

通过之前的配置，目前已经将elasticsearchClient 注入了容器中，后续只要引入即可

	@Autowired
    ElasticsearchClient elasticsearchClient;

还不知道怎么注入elasticsearchClient的去看我上篇文章
Elasticsearch-06-Elasticsearch Java API Client-Elasticsearch 8.0 的基础配置和使用

2：查询所有索引

//省略连接...
        final GetIndexResponse all = client.indices().get(query -> query.index("_all"));
        System.out.println(all.toString());
//省略关闭...

3：查询某个索引

        //查询某个索引
        final GetIndexResponse products = client.indices().get(query -> query.index("products"));
        System.err.println(products.toString());

4:创建索引

		//查询某个索引是否存在
        boolean exists = client.indices().exists(query -> query.index("products")).value();
        System.out.println(exists);
        if (exists) {
            System.err.println("索引已存在");

        } else {
            final CreateIndexResponse products = client.indices().create(builder -> builder.index("products"));
            System.err.println(products.acknowledged());
        }

5:删除指定索引

        //删除指定索引
        boolean exists = client.indices().exists(query -> query.index("products")).value();
        System.out.println(exists);
        if (exists) {
            DeleteIndexResponse response = client.indices().delete(query -> query.index("products"));
            System.err.println(response.acknowledged());
        } else {
            System.err.println("索引不存在");
        }

6:查询索引的映射

        //查询映射信息
        final GetIndexResponse response = client.indices().get(builder -> builder.index("produces"));
        System.err.println(response.result().get("produces").mappings());

7:创建索引指定映射

numberOfReplicas(“1”):设置副本
numberOfShards(“1”):设置分片

        //创建索引指定映射,分片和副本信息
        final CreateIndexResponse response = client.indices().create(builder ->
                builder.settings(indexSetting -> indexSetting.numberOfReplicas("1").numberOfShards("1")).mappings(
                        map -> map
                                .properties("name", propertyBuilder -> propertyBuilder.keyword(keywordProperty -> keywordProperty))
                                .properties("price", propertyBuilder -> propertyBuilder.double_(doubleNumProperty -> doubleNumProperty))
                                .properties("des", propertyBuilder -> propertyBuilder.text(textProperty -> textProperty.analyzer("ik_smart").searchAnalyzer("ik_smart")))
                ).index("produces")

        );

8:创建文档

使用HashMap作为数据存储容器

        //创建文档
        //1.创建HashMap进行存储数据，文档要对应映射
        final HashMap<String, Object> doc = new HashMap<>();
        doc.put("name","辣条");
        doc.put("age",12);
        doc.put("id","11111");
        //2.将文档存入索引中
        final IndexResponse response = client.index(builder -> builder.index("produces").id(doc.get("id")).document(doc));
        System.err.println(response.version());

使用自定义类作为数据存储容器

实体类

@Data
@AllArgsConstructor
@NoArgsConstructor
@ToString
public class Produce {
    private String id;
    private String name;
    private double age;
}

        //创建文档
        final Produce produce = new Produce("123", "小明", 18);
        final IndexResponse response = client.index(builder -> builder.index("produces").id(produce.getId()).document(produce));
        System.err.println(response.version());

使用外部JSON数据创建

这里要注意我们需要使用StringReader进行读取时使用replace函数将设置的’改为",当然这在真实的业务中肯定不会有,因为真实业务中一定是标准的JSON数据,无需使用replace进行替换了

        //创建文档
        final StringReader input = new StringReader(
                "{'name':'农夫三拳','price':3.00,'des':'农夫三拳有点甜'}".replace('\'', '"')
        );
        final IndexResponse response = client.index(builder -> builder.index("produces").id("44514").withJson(input));
        System.err.println(response.version());

9: 查询所有文档

 final SearchResponse<Object> response = client.search(builder -> builder.index("produces"), Object.class);
        final List<Hit<Object>> hits = response.hits().hits();
        hits.forEach(
                x-> System.err.println(x)
        );

10:根据ID查询文档

使用HashMap对应查询

        //查询文档
        final GetResponse<Map> response = client.get(builder -> builder.index("produces").id("116677"), Map.class);
        final Map source = response.source();
        source.forEach((x,y)->{
            System.err.println(x+":"+y);
        });

使用自定义类对应查询

        final GetResponse<Produce> response1 = client.get(builder -> builder.index("produces").id("aabbcc123"), Produce.class);
        final Produce source1 = response1.source();
        System.err.println(source1.toString());

11:删除文档

        final GetResponse<Produce> response1 = client.get(builder -> builder.index("produces").id("aabbcc123"), Produce.class);
        final Produce source1 = response1.source();
        System.err.println(source1.toString());

12:修改文档

全覆盖

        //修改文档（覆盖）
        final Produce produce = new Produce("ccaabb123", "旺仔摇滚洞", "旺仔摇滚洞乱摇乱滚", 10.23D);
        final UpdateResponse<Produce> response = client.update(builder -> builder.index("produces").id("aabbcc123").doc(produce), Produce.class);
        System.err.println(response.shards().successful());

修改部分文档

区别在于我们需要设置.docAsUpsert(true)表明是修改部分而不是覆盖

        //修改文档(部分修改)
//        final Produce produce = new Produce("ccaabb123", "旺仔摇滚洞", "旺仔摇滚洞乱摇乱滚", 10.23D);
        final Produce produce = new Produce();
        produce.setName("旺仔摇不动");
        final UpdateResponse<Produce> response = client.update(builder -> builder.index("produces").id("aabbcc123").doc(produce).docAsUpsert(true), Produce.class);
        System.err.println(response.shards().successful());

13:批量操作

批量新增

		produceList.add(produce1);
        produceList.add(produce2);
        produceList.add(produce3);
        //构建BulkRequest
        final BulkRequest.Builder br = new BulkRequest.Builder();
        for (Produce produce : produceList) {
            br.operations(op->op.index(idx->idx.index("produces").id(produce.getSku()).document(produce)));
        }
        final BulkResponse response = client.bulk(br.build());

批量删除

List<BulkOperation> bulkOperations = new ArrayList<>();
            // 向集合中添加需要删除的文档id信息
            for (int i = 0; i < dto.getIds().size(); i++) {
                int finalI = i;
                bulkOperations.add(BulkOperation.of(b -> b
                        .delete((d -> d
                                .index(dto.getIndex())
                                .id(dto.getIds().get(finalI))
                        ))
                ));
            }
            // 调用客户端的bulk方法，并获取批量操作响应结果
            BulkResponse response = client
                    .bulk(e -> e
                            .index(dto.getIndex())
                            .operations(bulkOperations));

批量更新

JSONObject jsonObject = new JSONObject();
            jsonObject.put("id", deleteIds);
            jsonObject.put("status", 1);

            BulkRequest.Builder br = new BulkRequest.Builder();
            for (String deleteId : deleteIds) {
                br.operations(op -> op
                        .update(idx ->
                                idx.index(EsIndexConstants.opinion_information)
                                        .id(deleteId)
                                        .action(a -> a
                                                .doc(jsonObject)//局部修改
                                                .docAsUpsert(true)//局部修改
                                        )
                        )).refresh(Refresh.True);
            }

            BulkRequest bulkRequest = br.build();
            BulkResponse result = null;
            try {
                result = elasticsearchClient.bulk(bulkRequest);
            } catch (IOException e) {
                throw new RuntimeException(e);
            }

DSL查询

1：matchAll查询所有文档

        //matchAll
        final SearchResponse<Produce> response = client.search(builder ->
                builder.index("produces")
                        .query(q ->
                                q.matchAll(
                                        v->v
                                )), Produce.class);

        System.err.println(response.hits().hits());

2:match 根据字段查询

        //简单query方式查询
        final SearchResponse<Produce> response = client.search(builder ->
                builder.index("produces")
                        .query(q ->
                                q.match(t ->
                                        t.field("name")
                                                .query("龙虎万精油"))), Produce.class);
        System.err.println(response.hits().hits());

3:多id查询

        //多ID查询
        final SearchResponse<Produce> response = client.search(builder ->
                builder.index("produces")
                        .query(q ->
                                q.ids(sid->sid.values("1000","1001"))), Produce.class);
        System.err.println(response.hits().hits());

4:term 不分词查询

        //term不分词条件查询
        final SearchResponse<Produce> response = client.search(builder -> builder.index("produces")
        .query(q -> q.term(t -> t.field("name").value("风油精"))), Produce.class);
        System.err.println(response.hits().hits());

5:范围查询

        //范围查询
        final SearchResponse<Produce> response = client.search(builder ->
                        builder.index("produces").query(q ->
                                q.range(r ->
                                        r.field("price").gt(JsonData.of(5D)).lt(JsonData.of(15D)))),
                Produce.class);
        System.err.println(response.hits().hits());

6: 前缀查询

  final SearchResponse<Produce> response = client.search(builder ->
                        builder.index("produces").query(q ->q.prefix(p->p.field("name").value("六"))),
                Produce.class);
        System.err.println(response.hits().hits());

7:匹配查询

//匹配查询

  final SearchResponse<Produce> response = client.search(builder ->
                        builder.index("produces").query(q ->q.wildcard(w->w.field("name").value("风*"))),
                Produce.class);
        System.err.println(response.hits().hits());

?单字符匹配

        //匹配查询
        final SearchResponse<Produce> response = client.search(builder ->
        builder.index("produces").query(q ->q.wildcard(w->w.field("name").value("风?精"))),
                Produce.class);
        System.err.println(response.hits().hits());

8:模糊查询

        //模糊查询
        final SearchResponse<Produce> response = client.search(builder ->
                        builder.index("produces").query(q ->q.fuzzy(f->f.field("name").value("六仙花露水"))),
                Produce.class);
        System.err.println(response.hits().hits());

9:多条件查询

使用bool关键字配合must,should,must_not

must:所有条件必须同时成立
must_not:所有条件必须同时不成立
should:所有条件中成立一个即可

        //多条件
        final SearchResponse<Produce> response = client.search(builder ->
                        builder.index("produces").query(q ->
                                q.bool(b ->
                                        b.must(t ->
                                                t.term(v ->
                                                        v.field("name")
                                                                .value("旺仔摇不动")))
                                         .must(t2 ->
                                                 t2.term(v2 ->
                                                        v2.field("price")
                                                                 .value(0.0D))))),
                Produce.class);
        System.err.println(response.hits().hits());

或者创建BoolQuery.Builder，以便进行业务判断是否增加查询条件

 List<FieldValue> fieldValues = new ArrayList<>();
        fieldValues.add(FieldValue.of(10));
        fieldValues.add(FieldValue.of(100));
        BoolQuery.Builder boolQuery = new BoolQuery.Builder();

        boolQuery.must(t->
                t.terms(v->
                        v.field("label")
                                .terms(term->
                                        term.value(fieldValues))));
        boolQuery.must(t->
                t.match(f->
                        f.field("name")
                                .query("旺仔")));


        SearchResponse<Object> search = elasticsearchClient.search(builder -> builder.index("my_test_index")
                .query(q->
                        q.bool(boolQuery.build())),Object.class);

10：多字段查询-multiMatch

        //多字段查询
        final SearchResponse<Produce> response = client.search(builder ->
                        builder.index("produces").query(q->q.multiMatch(qs->qs.query("蚊虫叮咬 辣眼睛").fields("name","des"))),
                Produce.class);
        System.err.println(response.hits().hits());

11:高亮显示

我们注意要设置前缀和后缀

        //高亮显示
        final SearchResponse<Produce> response = client.search(builder ->
                        builder.index("produces")
                                .query(q -> q.match(v -> v.field("name").query("风油精")))
                                .highlight(h -> h.preTags("<span>").postTags("<span>").fields("name", hf -> hf)),
                Produce.class);
        System.err.println(response.toString());

12:分页查询

我们使用match_all进行全部搜索的时候使用size关键字设置每一页的大小,使用from关键字设置页码
from的计算公式:(页码-1)*size

        //分页查询
                final SearchResponse<Produce> response = client.search(builder ->
                        builder.index("produces")
                                .query(q->q.matchAll(v->v)).size(2).from(0),
                Produce.class);
        System.err.println(response.hits().hits());

12-1：使用分页时，最多返回10000条。需要进行设置

        //分页查询
                final SearchResponse<Produce> response = client.search(builder ->
                        builder.index("produces")
                                .query(q->q.matchAll(v->v))
                                .size(2)
                                .from(0)
                                .trackTotalHits(t->t.enabled(true)),
                Produce.class);
        System.err.println(response.hits().hits());

13:排序

使用sort关键字指定需要进行排序的字段设置排序类型即可,我们这里会使用到SortOrder枚举类来进行指定排序方式

desc:降序
asc:升序

        //排序
        final SearchResponse<Produce> response = client.search(builder ->
                        builder.index("produces")
                                .query(q->q.matchAll(v->v))
                                .sort(builder1 -> builder1.field(f->f.field("price").order(SortOrder.Asc))),
                Produce.class);
        System.err.println(response.hits().hits());

14:指定字段查询

使用_source关键字在数组中设置需要展示的字段
值得注意的是在source方法中需要我们写filter去指定是include包含或是exclude去除xx字段

        //指定字段查询
        final SearchResponse<Produce> response = client.search(builder ->
                        builder.index("produces")
                                .query(q->q.matchAll(v->v))
                                .source(s->s.filter(v->v.includes("price","des"))),
                Produce.class);
        System.err.println(response.hits().hits());

15:聚合查询-求最大值

SearchResponse<Object> search = elasticsearchClient.search(builder ->
                builder.index("my_test_index")
                        .from(0)
                        .size(1)
                        .aggregations("aa", t ->
                                t.max(f->
                                        f.field("type"))), Object.class);
        EsResult esResult = EsUtils.searchAnalysis(search);
        Aggregate aa = esResult.getAggregations().get("aa");
        LongTermsAggregate lterms = aa.lterms();
        Buckets<LongTermsBucket> buckets = lterms.buckets();
        List<LongTermsBucket> array = buckets.array();

16:桶聚合查询-劣势 group by

SearchResponse<JSONObject> search = elasticsearchClient.search(builder ->
                    builder.index(EsIndexConstants.article_info)
                            .query(t->
                                    t.range(f->
                                            f.field("create_time")
                                                    .gte(JsonData.of(startDate))
                                                    .lte(JsonData.of(endDate))))
                            .from(0)
                            .size(1)
                            .aggregations("countValue", t ->
                                    t.terms(f -> f.field("ata_type.keyword")))
                            , JSONObject.class);
Aggregate countValue = search .getAggregations().get("countValue");
List<StringTermsBucket> array = countValue.sterms().buckets().array();